explore_result

One-page viewer for a <code>genetic_algorithm()</code> result: Leaflet
map of that generation's best layout (downwind wake cones, optional
terrain layers), a wind rose, and one plotly figure with fitness,
operator rates and population. New fitness maxima are marked; click
a marker to jump to that generation. The cell heatmap is not
included: use <code>plot_cell_heatmap()</code> or <code>plot_generation()</code> offline.
Requires Suggests <code>shiny</code>. Plotly is used when installed.

The genetic algorithm is designed to optimize wind farms of any shape. Each layout is encoded as n unique grid-cell identifiers. It requires a predefined amount of turbines, a unified rotor radius and an average wind speed value for each incoming wind direction. A terrain effect model can be included that downloads an 'SRTM' elevation model and loads a Corine Land Cover raster to approximate surface roughness.

Sebastian Gatscha

windfarmGA

Genetic Algorithm for Wind Farm Layout Optimization

explore_result function

<dl><dt>result</dt>
<dd>The output of <code>genetic_algorithm</code></dd>
<dt>area</dt>
<dd>Site polygon (<code>sf</code>, SpatialPolygons, or coordinate matrix).
Must be projected in metres.</dd></dl>

Arguments

Shiny explorer for a GA result — explore_result

<dl>

<dt>result</dt>
<dd>The output of <code>genetic_algorithm</code></dd>


<dt>area</dt>
<dd>Site polygon (<code>sf</code>, SpatialPolygons, or coordinate matrix).
Must be projected in metres.</dd>

</dl>

explore_result: Shiny explorer for a GA result

Description

Usage

Value

Arguments

Examples